Effects of spatial aggregation on the multi-scale estimation of evapotranspiration

Handle URI:
http://hdl.handle.net/10754/562697
Title:
Effects of spatial aggregation on the multi-scale estimation of evapotranspiration
Authors:
Ershadi, Ali; McCabe, Matthew ( 0000-0002-1279-5272 ) ; Evans, Jason P.; Walker, Jeffrey P.
Abstract:
The influence of spatial resolution on the estimation of land surface heat fluxes from remote sensing is poorly understood. In this study, the effects of aggregation from fine (< 100 m) to medium (approx. 1. km) scales are investigated using high resolution Landsat 5 overpasses. A temporal sequence of satellite imagery and needed meteorological data were collected over an agricultural region, capturing distinct variations in crop stage and phenology. Here, we investigate both the impact of aggregating the input forcing and of aggregating the derived latent heat flux. In the input aggregation scenario, the resolution of the Landsat based radiance data was increased incrementally from 120. m to 960. m, with the land surface temperature calculated at each specific resolution. Reflectance based land surface parameters such as vegetation height and leaf area index were first calculated at the native 30. m Landsat resolution and then aggregated to multiple spatial scales. Using these data and associated meteorological forcing, surface heat fluxes were calculated at each distinct resolution using the Surface Energy Balance System (SEBS) model. Results indicate that aggregation of input forcing using a simple averaging method has limited effect on the land surface temperature and available energy, but can reduce evapotranspiration estimates at the image scale by up to 15%, and at the pixel scale by up to 50%. It was determined that the predominant reason for the latent heat flux reduction in SEBS was a decrease in the aerodynamic resistance at coarser resolutions, which originates from a change in the roughness length parameters of the land surface due to the aggregation. In addition, the magnitude of errors in surface heat flux estimation due to input aggregation was observed to be a function of the heterogeneity of the land surface and evaporative elements. In examining the response of flux aggregation, fine resolution (120. m) heat fluxes were aggregated to coarser resolutions using a range of common spatial interpolation algorithms. Results illustrate that a simple averaging scheme provides the best choice for flux aggregation compared to other approaches such as nearest neighbour, bilinear interpolation or bicubic interpolation, as it not only preserves the spatial distribution of evapotranspiration, but most importantly also conserves the mass balance of evaporated water across pixel and image scales. © 2012 Elsevier Inc.
KAUST Department:
Water Desalination and Reuse Research Center (WDRC); Biological and Environmental Sciences and Engineering (BESE) Division; Environmental Science and Engineering Program; Earth System Observation and Modelling
Publisher:
Elsevier
Journal:
Remote Sensing of Environment
Issue Date:
Apr-2013
DOI:
10.1016/j.rse.2012.12.007
Type:
Article
ISSN:
00344257
Appears in Collections:
Articles; Environmental Science and Engineering Program; Water Desalination and Reuse Research Center (WDRC); Biological and Environmental Sciences and Engineering (BESE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorErshadi, Alien
dc.contributor.authorMcCabe, Matthewen
dc.contributor.authorEvans, Jason P.en
dc.contributor.authorWalker, Jeffrey P.en
dc.date.accessioned2015-08-03T11:01:57Zen
dc.date.available2015-08-03T11:01:57Zen
dc.date.issued2013-04en
dc.identifier.issn00344257en
dc.identifier.doi10.1016/j.rse.2012.12.007en
dc.identifier.urihttp://hdl.handle.net/10754/562697en
dc.description.abstractThe influence of spatial resolution on the estimation of land surface heat fluxes from remote sensing is poorly understood. In this study, the effects of aggregation from fine (< 100 m) to medium (approx. 1. km) scales are investigated using high resolution Landsat 5 overpasses. A temporal sequence of satellite imagery and needed meteorological data were collected over an agricultural region, capturing distinct variations in crop stage and phenology. Here, we investigate both the impact of aggregating the input forcing and of aggregating the derived latent heat flux. In the input aggregation scenario, the resolution of the Landsat based radiance data was increased incrementally from 120. m to 960. m, with the land surface temperature calculated at each specific resolution. Reflectance based land surface parameters such as vegetation height and leaf area index were first calculated at the native 30. m Landsat resolution and then aggregated to multiple spatial scales. Using these data and associated meteorological forcing, surface heat fluxes were calculated at each distinct resolution using the Surface Energy Balance System (SEBS) model. Results indicate that aggregation of input forcing using a simple averaging method has limited effect on the land surface temperature and available energy, but can reduce evapotranspiration estimates at the image scale by up to 15%, and at the pixel scale by up to 50%. It was determined that the predominant reason for the latent heat flux reduction in SEBS was a decrease in the aerodynamic resistance at coarser resolutions, which originates from a change in the roughness length parameters of the land surface due to the aggregation. In addition, the magnitude of errors in surface heat flux estimation due to input aggregation was observed to be a function of the heterogeneity of the land surface and evaporative elements. In examining the response of flux aggregation, fine resolution (120. m) heat fluxes were aggregated to coarser resolutions using a range of common spatial interpolation algorithms. Results illustrate that a simple averaging scheme provides the best choice for flux aggregation compared to other approaches such as nearest neighbour, bilinear interpolation or bicubic interpolation, as it not only preserves the spatial distribution of evapotranspiration, but most importantly also conserves the mass balance of evaporated water across pixel and image scales. © 2012 Elsevier Inc.en
dc.publisherElsevieren
dc.subjectAerodynamic resistanceen
dc.subjectFlux aggregationen
dc.subjectInput aggregationen
dc.subjectLand surface temperatureen
dc.subjectLandsaten
dc.subjectMODISen
dc.subjectRoughnessen
dc.subjectSurface Energy Balance System (SEBS)en
dc.subjectUncertaintyen
dc.subjectUpscalingen
dc.titleEffects of spatial aggregation on the multi-scale estimation of evapotranspirationen
dc.typeArticleen
dc.contributor.departmentWater Desalination and Reuse Research Center (WDRC)en
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Divisionen
dc.contributor.departmentEnvironmental Science and Engineering Programen
dc.contributor.departmentEarth System Observation and Modellingen
dc.identifier.journalRemote Sensing of Environmenten
dc.contributor.institutionSchool of Civil and Environmental Engineering, The University of NSW, Sydney, Australiaen
dc.contributor.institutionClimate Change Research Centre, The University of NSW, Sydney, Australiaen
dc.contributor.institutionDepartment of Civil Engineering, Monash University, Clayton, Australiaen
kaust.authorMcCabe, Matthewen
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